An entropy weight-based method for path loss predictions for terrestrial services in the VHF and UHF bands

VHF and UHF are widely used frequency bands, and accurate path loss prediction in these bands is of great significance. In order to improve the prediction accuracy and stability of radio wave propagation, we propose a combined modeling method based on the entropy weight method. This method assigns appropriate weights to the predicted values of sub-models using entropy, and calculates the final predicted value through weighted aggregation. To validate the feasibility of our proposed method, we conduct modeling using data from Denver, Colorado. We compare our method with the ITU-R models and a model established using the coefficient of variation method. The results demonstrate that our proposed model outperforms the compared models. Specifically, the root-mean-square error (RMSE) of our proposed model is reduced by 5.94 and 5.51 dB compared to the ITU-R P.1546 and 2001 models, respectively. Moreover, our proposed model exhibits better stability than the ITU-R models. We also use the improvement percentage (γ) to evaluate the degree of improvement of our model over the sub-models, which is 49.13% and 47.86% for the ITU-R P.1546 and 2001 models, respectively. Additionally, by comparing the RMSE and absolute error, we find that the entropy weight-based method outperforms the coefficient of variation-based method. This research demonstrates the superiority of the entropy weight-based modeling method, providing a valuable channel modeling approach for path loss prediction and supporting the regional assimilation of radio propagation prediction methods.